Responsible for delivering high-quality work products within defined timelines while providing technical leadership to the PlainID team.
Compensation
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. A reasonable estimate of the current range is $113,300 to $188,900.
Responsibilities
Configure and implement the PlainID Authorization Platform within client environments
Lead technical discussions with Enterprise architects and IAM stakeholders
Design and develop generative AI solutions for clients within PwC’s Advisory practice using Azure-based engineering, Python, and large language model APIs.
Compensation
The salary range for this position is: $77,000 - $202,000. Actual compensation within the range will be dependent upon the individual's skills, experience, qualifications and location, and applicable employment laws. All hired individuals are eligible for an annual discretionary bonus.
Responsibilities
Design Azure-based generative AI architectures and analytical models
Build conversational applications with Azure AI Services, Azure OpenAI Service, LLM APIs, prompt engineering, and context engineering
Develop retrieval-augmented generation pipelines using data modeling, information retrieval systems, and vector databases
Orchestrate AI agents with LangGraph, LangChain, and Model Context Protocol
Create cloud-native microservices in Python, C#, and JavaScript, integrating AI capabilities with existing applications
Lead design and delivery of agentic and generative AI solutions for clients within an advisory practice, managing client workstreams, budgets, and technical architecture on Microsoft Azure.
Compensation
The salary range for this position is: $124,000 - $280,000. Actual compensation within the range will be dependent upon the individual's skills, experience, qualifications and location, and applicable employment laws. All hired individuals are eligible for an annual discretionary bonus.
Responsibilities
Leading client workstreams to design agentic and generative AI solutions on Microsoft Azure, translating business needs into technical architecture, delivery plans, budgets, and milestones
Designing agent orchestration and conversational workflows with LangChain, LangGraph, Model Context Protocol, and LLM APIs, incorporating context and prompt engineering
Developing retrieval-augmented generation pipelines using vector databases, natural language processing, and data science methods to ground model responses in client data
Directing implementation with Azure AI Services, Azure OpenAI Service, Python, and C#, connecting AI capabilities to Azure-native applications and APIs
Overseeing deployment and maintenance through LLMOps, Azure Kubernetes Service, Azure API Management, and cloud identity and access management, including operational monitoring
Lead assessment and scoring workshops across ServiceNow-led, Salesforce-led and hybrid cloud-native options, including demos, scenario walkthroughs and stakeholder sessions.
Locations (6)
Atlanta, Georgia, United States
Dallas, Texas, United States
Houston, Texas, United States
New Jersey, New Jersey, United States
Nashville, Tennessee, United States
Vice President - Technology (Senior Data & AI Infrastructure Platform Engineer)
The PJT Partners Technology team is responsible for creating and continuously improving a robust and secure technology foundation that supports the firm’s business activities. Our Technology team is seeking a Data and AI Infrastructure Engineer to build secure, scalable platforms and pipelines that power the firm’s AI initiatives. This is a platform engineering role — the focus is building the infrastructure and developer tooling that enables teams to rapidly develop and deploy AI-powered Python applications using Azure AI Foundry and the Claude API (Anthropic), not training custom models.
Compensation
Expected annualized base salary of $175,000 to $215,000.
Responsibilities
Design, build, and operate the firm’s AI platform, enabling developers to build and deploy Python-based AI applications
Implement and manage Azure AI Foundry environments: model deployments, AI hubs, project workspaces, and access controls
Integrate and operationalize third-party AI APIs (Anthropic Claude API, Azure OpenAI) with secure access patterns, API gateway controls, rate limiting, and cost monitoring
Build internal developer tooling and SDK scaffolding to accelerate AI application development across the firm
Build and maintain data pipelines using Azure Data Factory and Azure Databricks to serve AI application data needs
Lead governance and operational management of the Firm’s enterprise AI platforms, establishing guardrails, controls, and operating practices to support secure, responsible, scalable, and cost‑effective AI adoption.
Compensation
It is expected that the base salary range for this position will be $115,000 to $180,000.
Responsibilities
Lead governance, administration and operational oversight of the Firm's enterprise AI platforms
Establish and maintain platform governance frameworks, standards, controls, guardrails, escalation processes and operating procedures
Translate cybersecurity, identity, privacy, data governance, legal and compliance requirements into effective platform configurations and controls
Govern AI and agent lifecycles, including registration, classification, approval, deployment, monitoring, recertification and retirement
Seeking a skilled DevOps Engineer to help optimize DevOps practices, ensure the reliability and performance of technology infrastructure, streamlineine API management, and enhance cross-team collaboration.
Compensation
The pay range for this position is $50.00 - $80.00/hr.
Responsibilities
Lead and support the migration of API endpoints from MuleSoft to Azure API Management (APIM), including setup, monitoring, and performance optimization
Build, maintain, and optimize CI/CD pipelines for various in-house and SaaS applications
Collaborate with DevOps team members to standardize processes and tools across multiple workstreams
Provide L3 support for infrastructure and application-related projects
Contribute to cross-training initiatives and help develop a more unified DevOps practice
Design, develop, and operate middleware solutions that enable secure, scalable communication between enterprise applications and external service providers.
Compensation
Salary Pay Range: $116,300.00 -$155,100.00
Responsibilities
Design and develop integration services and APIs using TypeScript and Node.js.
Build and maintain serverless workloads with Azure Functions and workflow automations with Azure Logic Apps.
Configure and manage API publishing, security, policies, and lifecycle practices with Azure API Management.
Integrate enterprise applications, internal platforms, and external providers through well-defined APIs and resilient messaging or workflow patterns.
Use Azure platform services to support secure, scalable, and highly available integration solutions.
Requirements
Bachelor’s Degree in Software Engineering, Computer Science, or related fields
Healthcare Interoperability Engineer role focused on FHIR mapping, CMS stabilization, and provider integration patterns using Azure.
Compensation
Rate: $40 - 50
Responsibilities
CMS-0057 production stabilization
Address priority production issues and simplify/refine the FHIR mapping, provider mapping, routing, exception-handling, and integration components based on actual transaction behavior.
Design and implement prioritized CMS-0057 Day 2 and BCBSA fast-follow capabilities planned for Q1 and Q2 2027.
Establish reusable technical patterns for provider connectivity and bi-directional FHIR/API exchange that can be leveraged by Blueprint provider and EMR/EHR initiatives.
Expand automated conformance, regression, negative-path, and end-to-end testing to reduce manual validation and improve release confidence.
The base compensation range for this role in the posted location is: $109,180 - 197,175.
Responsibilities
Lead assessment and scoring workshops across ServiceNow-led, Salesforce-led and hybrid cloud-native options, including demos, scenario walkthroughs and stakeholder sessions.
Set the evaluation criteria across functional fit, architecture, AI, implementation, financials and strategic alignment.
Produce weighted scorecards with clear recommendations, risks, trade-offs and a business case executives can act on.
Assess mobile field-service options: Salesforce Field Service, ServiceNow FSM and Neuron7.
Design reference architectures covering service models, integration patterns and security controls.
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